“Internet of things“, “edge computing” and “artificial intelligence” have been popular for some time. These words can be seen everywhere, but everyone’s understanding and definition behind these nouns may be different or even confused.
When understanding the contents of these terms, many people tend to over boast the technical content behind them and exaggerate the concepts. We believe that the real value behind these terms is to show how to connect different technologies through the example of smart city and other embedded concepts. However, explaining artificial intelligence in real life may be complicated because it is a system containing many interconnected components, not just devices loaded with intelligent software.
Therefore, before explaining these nouns, it is necessary to fully define the nouns related to this article:
IoT, Internet of Thing
The Internet of things has been widely used in various fields, and all walks of life have reached a certain consensus on its definition. It generally refers to “things” interconnected through the network (usually the Internet). In this case, the “thing” referred to does not strictly refer to individual electronic devices, but also clothing (such as wearable electronic products), or even people wearing heart rhythm regulators and similar devices. Therefore, basically, the application mode of each chip transmitting data in the network can be regarded as the application category of the Internet of things.
The original concept of the Internet of things needs to send data to the cloud for processing and analysis. However, with the significant increase in the number of interconnected devices, many application modes encounter a problem, that is, a large number of round-trip transmission will lead to data delay. Therefore, in order to solve the limitations of cloud computing on the future development of the Internet of things, edge computing has become one of the important technologies to support the continuous diffusion of the Internet of things. By analyzing data at the edge, the device can determine which content needs to be sent to the cloud and which content can be filtered. In short, edge operation refers to moving the computing force from the center to the edge, which will greatly increase the system operation efficiency.
Artificial Intelligence (AI)
Strictly speaking, the artificial intelligence we currently use is still within the scope of the concept of “narrow artificial intelligence”, which means that a program or system can perform a specific set of tasks without any direct manual input, such as using machine learning to realize text, picture and speech recognition technology, Deal with thousands (or even millions) of different data and learn how to distinguish different inputs.
Intelligent Internet of things, as its name implies, is formed by combining artificial intelligence and Internet of things technology. This can be seen as moving artificial intelligence to the edge, so that a larger computing range occurs in the location of Internet of things devices. You can imagine a monitoring system running facial recognition. Instead of delaying sending data to the cloud for analysis, it changes the data to be analyzed directly by local artificial intelligence devices.
UAV traffic monitoring
With the continuous development of our urban roads, the problem of traffic jam is getting worse and worse. Therefore, using real-time data to monitor and change traffic flow can significantly improve efficiency and improve traffic congestion. Through the erection of smart street lights, the traffic flow can be monitored in each road section and the traffic signals can be adjusted in time, or UAVs can be used as a higher deployment option for mobility, and a wider range of areas can be monitored. The smart street lights can be used to collect information in real time and then sent to nearby devices for analysis.
In the first step, the analysis is processed by the edge artificial intelligence platform. This includes vehicle identification and traffic flow assessment. Therefore, the device can judge how to process the data by itself according to the analysis. For example, is the number of vehicles increasing? Is there a risk of traffic jam? Then, the basic data will be sent to a centralized platform (or cloud), where measures such as dredging traffic, changing speed limit and adjusting traffic lights will be taken according to the data to manage traffic problems in the city.
Most data processing will be carried out in the cloud, and edge computing will be more and more widely used. Although Internet of things devices have more powerful computing power, the network bandwidth is still limited. The ongoing 5g infrastructure can effectively solve the problem of data transmission delay and greatly improve real-time analysis to meet the requirements of smart Internet of things workload.
Fleet management and artificial intelligence
In terms of vehicle management, artificial intelligence can also strengthen the operation business of fleet management. Managing large fleets can be quite challenging, and there are many ways to optimize operations: reducing fuel costs, reducing unsafe driving behavior, vehicle maintenance and so on.
At present, most vehicle positioning systems rely heavily on global positioning system. You may have experienced the situation that GPS completely loses its positioning ability when entering the tunnel. This may also happen in urban areas when vehicles drive into indoor parking lots or other areas with poor satellite coverage. In addition, the positioning system is also difficult to locate the altitude of the vehicle.
In fact, in addition to GPS, there are other data sources that can help us locate the vehicle. For example, each vehicle itself can continuously track vehicle speed and turning range. Then, the artificial intelligence platform on the vehicle can use these parameters to supplement the missing or incomplete positioning data and calculate the vehicle position at any time. This technology is called vehicle dead reckoning, or Dr for short. Finally, the data can also be transmitted back to the traffic control personnel through wireless network.
This is the way that the artificial intelligence device can assist the traffic control personnel to track the vehicle position even if it is not within the line of sight of the satellite. Imagine this situation: a car has an accident in the tunnel, but if the vehicle is only equipped with a basic GPS tracking system, the traffic control personnel still have no way to know that the accident has occurred, unless they get in touch through some way. However, if the artificial intelligence tracking system is used, the traffic control personnel will be notified immediately if the vehicle does not move, the engine suddenly stops, or something goes wrong.
Storage and memory – fundamentals of smart IOT system
Many discussions on Intelligent Internet of things tend to focus on artificial intelligence and machine learning. However, artificial intelligence and the Internet of things are not only hardware with AI algorithms, or magic boxes that can be used everywhere, but should be regarded as an intelligent system composed of many intelligent basic components. Storage, memory and other components are in each node of data transmission, which occupies the most basic role in the intelligent system. Compared with the past, the basic components applied in smart IOT will play a more and more important role as the amount of data stored by terminal devices will be more and more. For example, first of all, if the asset security protection capability of this link is insufficient, it may endanger the overall system. In view of this market demand, Yiding further binds SSDs to the system. In this design, SSDs can only be paired with the bound system, but can not be accessed when installed in other systems. This method requires both system and SSD manufacturers to have a certain degree of data encryption technology in order to read and write data safely and quickly.
In addition, aiot is applied in various specific fields, and the systems in each field have their special requirements and corresponding functions. SSD manufacturers must be able to cooperate with them to design applicable systems according to their characteristics. In addition to memory technology, it also requires professional knowledge in various fields, including accurate and real-time data processing when applied in specific fields, so as to meet the intelligent requirements.
At present, the smart Internet of things is still a hot topic. Therefore, when evaluating this technology, it is necessary to distinguish which technologies are feasible at present and which exist in the future. Aiot has a huge architecture, multiple applications and requires a lot of expertise. It is impossible for a single manufacturer to complete all configurations. Yiding International Group has rapidly introduced system design and built a fast and perfect aiot through professional division and cooperation in their respective fields.